diff --git a/.Rbuildignore b/.Rbuildignore
index ec2b02aa4a..c7366abf79 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -31,3 +31,5 @@
 ^\.devcontainer$
 ^vignettes/articles$
 ^inst/cheatsheet$
+^data-raw$
+^doc$
diff --git a/.gitignore b/.gitignore
index 2a6f8564ba..db7075c835 100644
--- a/.gitignore
+++ b/.gitignore
@@ -54,3 +54,5 @@ admiral*.tgz
 ._.DS_Store
 
 .Rprofile
+/doc/
+/Meta/
diff --git a/.lycheeignore b/.lycheeignore
index be3b4cf525..bcb04df144 100644
--- a/.lycheeignore
+++ b/.lycheeignore
@@ -7,3 +7,4 @@ https://raw.githubusercontent.com/pharmaverse/admiral/main/inst/cheatsheet/cheat
 https://rsc.niaid.nih.gov/clinical-research-sites/daids-adverse-event-grading-tables
 https://rsc.niaid.nih.gov/sites/default/files/daidsgradingcorrectedv21.pdf
 https://www.fda.gov/media/116737/download
+
diff --git a/NEWS.md b/NEWS.md
index 7bb95dc688..91fb0405c8 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -42,6 +42,8 @@
 <details>
 <summary>Developer Notes</summary>
 
+- Adopted `data-raw/data` R Package Convention (#2427)
+
 </details>
 
 # admiral 1.1.1
diff --git a/data-backup/admiral_adlb.rda b/data-backup/admiral_adlb.rda
new file mode 100644
index 0000000000..9bf8663e65
Binary files /dev/null and b/data-backup/admiral_adlb.rda differ
diff --git a/data-backup/admiral_adsl.rda b/data-backup/admiral_adsl.rda
new file mode 100644
index 0000000000..79f5921fdb
Binary files /dev/null and b/data-backup/admiral_adsl.rda differ
diff --git a/data-raw/adlb_grading/adlb_grading_spec.xlsx b/data-raw/adlb_grading/adlb_grading_spec.xlsx
new file mode 100644
index 0000000000..426c5b4951
Binary files /dev/null and b/data-raw/adlb_grading/adlb_grading_spec.xlsx differ
diff --git a/data-raw/adlb_grading/atoxgr_sources.R b/data-raw/adlb_grading/atoxgr_sources.R
new file mode 100644
index 0000000000..90c833891a
--- /dev/null
+++ b/data-raw/adlb_grading/atoxgr_sources.R
@@ -0,0 +1,22 @@
+atoxgr_criteria <- system.file("adlb_grading/adlb_grading_spec.xlsx", package = "admiral")
+# Contrary to our usual convention the use of `::` here is explicit. This way we
+# avoid having to list {readxl} in "Imports" and instead get away with just
+# listing it in "Depends".
+
+atoxgr_criteria_ctcv4 <- atoxgr_criteria %>%
+  readxl::read_excel(sheet = "NCICTCAEv4") %>%
+  dplyr::mutate(GRADE_CRITERIA_CODE = gsub("[\r\n]", " ", GRADE_CRITERIA_CODE))
+
+usethis::use_data(atoxgr_criteria_ctcv4, overwrite = TRUE)
+
+atoxgr_criteria_ctcv5 <- atoxgr_criteria %>%
+  readxl::read_excel(sheet = "NCICTCAEv5") %>%
+  dplyr::mutate(GRADE_CRITERIA_CODE = gsub("[\r\n]", " ", GRADE_CRITERIA_CODE))
+
+use_data(atoxgr_criteria_ctcv5, overwrite = TRUE)
+
+atoxgr_criteria_daids <- atoxgr_criteria %>%
+  readxl::read_excel(sheet = "DAIDS") %>%
+  dplyr::mutate(GRADE_CRITERIA_CODE = gsub("[\r\n]", " ", GRADE_CRITERIA_CODE))
+
+use_data(atoxgr_criteria_daids, overwrite = TRUE)
diff --git a/data-raw/admiral_adlb.R b/data-raw/admiral_adlb.R
new file mode 100644
index 0000000000..f07345368b
--- /dev/null
+++ b/data-raw/admiral_adlb.R
@@ -0,0 +1,466 @@
+# Name: ADLB
+#
+# Label: Lab Analysis Dataset
+#
+# Input: adsl, lb
+# nolint start: undesirable_function_linter
+library(admiral)
+library(pharmaversesdtm) # Contains example datasets from the CDISC pilot project
+library(dplyr)
+library(lubridate)
+library(stringr)
+# nolint end
+
+# Load source datasets ----
+
+# Use e.g. haven::read_sas to read in .sas7bdat, or other suitable functions
+# as needed and assign to the variables below.
+# For illustration purposes read in admiral test data
+
+data("lb")
+data("admiral_adsl")
+
+adsl <- admiral_adsl
+
+# When SAS datasets are imported into R using haven::read_sas(), missing
+# character values from SAS appear as "" characters in R, instead of appearing
+# as NA values. Further details can be obtained via the following link:
+# https://pharmaverse.github.io/admiral/articles/admiral.html#handling-of-missing-values # nolint
+
+lb <- convert_blanks_to_na(lb)
+
+# Look-up tables ----
+
+# Assign PARAMCD, PARAM, and PARAMN
+param_lookup <- tibble::tribble(
+  ~LBTESTCD, ~PARAMCD, ~PARAM, ~PARAMN,
+  "ALB", "ALB", "Albumin (g/L)", 1,
+  "ALP", "ALKPH", "Alkaline Phosphatase (U/L)", 2,
+  "ALT", "ALT", "Alanine Aminotransferase (U/L)", 3,
+  "ANISO", "ANISO", "Anisocytes", 4,
+  "AST", "AST", "Aspartate Aminotransferase (U/L)", 5,
+  "BASO", "BASO", "Basophils Abs (10^9/L)", 6,
+  "BASOLE", "BASOLE", "Basophils/Leukocytes (FRACTION)", 7,
+  "BILI", "BILI", "Bilirubin (umol/L)", 8,
+  "BUN", "BUN", "Blood Urea Nitrogen (mmol/L)", 9,
+  "CA", "CA", "Calcium (mmol/L)", 10,
+  "CHOL", "CHOLES", "Cholesterol (mmol/L)", 11,
+  "CK", "CK", "Creatinine Kinase (U/L)", 12,
+  "CL", "CL", "Chloride (mmol/L)", 13,
+  "COLOR", "COLOR", "Color", 14,
+  "CREAT", "CREAT", "Creatinine (umol/L)", 15,
+  "EOS", "EOS", "Eosinophils (10^9/L)", 16,
+  "EOSLE", "EOSLE", "Eosinophils/Leukocytes (FRACTION)", 17,
+  "GGT", "GGT", "Gamma Glutamyl Transferase (U/L)", 18,
+  "GLUC", "GLUC", "Glucose (mmol/L)", 19,
+  "HBA1C", "HBA1C", "Hemoglobin A1C (1)", 20,
+  "HCT", "HCT", "Hematocrit (1)", 21,
+  "HGB", "HGB", "Hemoglobin (mmol/L)", 22,
+  "K", "POTAS", "Potassium (mmol/L)", 23,
+  "KETONES", "KETON", "Ketones", 24,
+  "LYM", "LYMPH", "Lymphocytes Abs (10^9/L)", 25,
+  "LYMLE", "LYMPHLE", "Lymphocytes/Leukocytes (FRACTION)", 26,
+  "MACROCY", "MACROC", "Macrocytes", 27,
+  "MCH", "MCH", "Ery. Mean Corpuscular Hemoglobin (fmol(Fe))", 28,
+  "MCHC", "MCHC", "Ery. Mean Corpuscular HGB Concentration (mmol/L)", 29,
+  "MCV", "MCV", "Ery. Mean Corpuscular Volume (f/L)", 30,
+  "MICROCY", "MICROC", "Microcytes", 31,
+  "MONO", "MONO", "Monocytes (10^9/L)", 32,
+  "MONOLE", "MONOLE", "Monocytes/Leukocytes (FRACTION)", 33,
+  "PH", "PH", "pH", 34,
+  "PHOS", "PHOS", "Phosphate (mmol/L)", 35,
+  "PLAT", "PLAT", "Platelet (10^9/L)", 36,
+  "POIKILO", "POIKIL", "Poikilocytes", 37,
+  "POLYCHR", "POLYCH", "Polychromasia", 38,
+  "PROT", "PROT", "Protein (g/L)", 39,
+  "RBC", "RBC", "Erythrocytes (TI/L)", 40,
+  "SODIUM", "SODIUM", "Sodium (mmol/L)", 41,
+  "SPGRAV", "SPGRAV", "Specific Gravity", 42,
+  "TSH", "TSH", "Thyrotropin (mU/L)", 43,
+  "URATE", "URATE", "Urate (umol/L)", 44,
+  "UROBIL", "UROBIL", "Urobilinogen", 45,
+  "VITB12", "VITB12", "Vitamin B12 (pmol/L)", 46,
+  "WBC", "WBC", "Leukocytes (10^9/L)", 47
+)
+
+
+# Derivations ----
+
+# Get list of ADSL vars required for derivations
+adsl_vars <- exprs(TRTSDT, TRTEDT, TRT01A, TRT01P)
+
+adlb <- lb %>%
+  # Join ADSL with LB (need TRTSDT for ADY derivation)
+  derive_vars_merged(
+    dataset_add = adsl,
+    new_vars = adsl_vars,
+    by_vars = exprs(STUDYID, USUBJID)
+  ) %>%
+  ## Calculate ADT, ADY ----
+  derive_vars_dt(
+    new_vars_prefix = "A",
+    dtc = LBDTC
+  ) %>%
+  derive_vars_dy(reference_date = TRTSDT, source_vars = exprs(ADT))
+
+adlb <- adlb %>%
+  ## Add PARAMCD PARAM and PARAMN - from LOOK-UP table ----
+  # Replace with PARAMCD lookup function
+  derive_vars_merged_lookup(
+    dataset_add = param_lookup,
+    new_vars = exprs(PARAMCD, PARAM, PARAMN),
+    by_vars = exprs(LBTESTCD),
+    check_type = "none",
+    print_not_mapped = FALSE
+  ) %>%
+  ## Calculate PARCAT1 AVAL AVALC ANRLO ANRHI ----
+  mutate(
+    PARCAT1 = LBCAT,
+    AVAL = LBSTRESN,
+    # Only populate AVALC if character value is non-redundant with AVAL
+    AVALC = ifelse(
+      is.na(LBSTRESN) | as.character(LBSTRESN) != LBSTRESC,
+      LBSTRESC,
+      NA
+    ),
+    ANRLO = LBSTNRLO,
+    ANRHI = LBSTNRHI
+  )
+
+# Derive Absolute values from fractional Differentials using WBC
+# Only derive where absolute values do not already exist
+# Need to populate ANRLO and ANRHI for newly created records
+adlb <- adlb %>%
+  # Derive absolute Basophils
+  derive_param_wbc_abs(
+    by_vars = exprs(STUDYID, USUBJID, !!!adsl_vars, DOMAIN, VISIT, VISITNUM, ADT, ADY),
+    set_values_to = exprs(
+      PARAMCD = "BASO",
+      PARAM = "Basophils Abs (10^9/L)",
+      PARAMN = 6,
+      DTYPE = "CALCULATION",
+      PARCAT1 = "HEMATOLOGY"
+    ),
+    get_unit_expr = extract_unit(PARAM),
+    diff_code = "BASOLE"
+  ) %>%
+  # Derive absolute Lymphocytes
+  derive_param_wbc_abs(
+    by_vars = exprs(STUDYID, USUBJID, !!!adsl_vars, DOMAIN, VISIT, VISITNUM, ADT, ADY),
+    set_values_to = exprs(
+      PARAMCD = "LYMPH",
+      PARAM = "Lymphocytes Abs (10^9/L)",
+      PARAMN = 25,
+      DTYPE = "CALCULATION",
+      PARCAT1 = "HEMATOLOGY"
+    ),
+    get_unit_expr = extract_unit(PARAM),
+    diff_code = "LYMPHLE"
+  )
+
+## Get Visit Info ----
+# See also the "Visit and Period Variables" vignette
+# (https://pharmaverse.github.io/admiral/articles/visits_periods.html#visits)
+adlb <- adlb %>%
+  # Derive Timing
+  mutate(
+    AVISIT = case_when(
+      str_detect(VISIT, "SCREEN") ~ "Baseline",
+      !is.na(VISIT) ~ str_to_title(VISIT),
+      TRUE ~ NA_character_
+    ),
+    AVISITN = case_when(
+      AVISIT == "Baseline" ~ 0,
+      !is.na(VISITNUM) ~ VISITNUM
+    )
+  )
+
+adlb <- adlb %>%
+  ## Calculate ONTRTFL ----
+  derive_var_ontrtfl(
+    start_date = ADT,
+    ref_start_date = TRTSDT,
+    ref_end_date = TRTEDT,
+    filter_pre_timepoint = AVISIT == "Baseline"
+  )
+
+## Calculate ANRIND : requires the reference ranges ANRLO, ANRHI ----
+adlb <- adlb %>%
+  derive_var_anrind()
+
+## Derive baseline flags ----
+adlb <- adlb %>%
+  # Calculate BASETYPE
+  mutate(
+    BASETYPE = "LAST"
+  ) %>%
+  # Calculate ABLFL
+  restrict_derivation(
+    derivation = derive_var_extreme_flag,
+    args = params(
+      by_vars = exprs(STUDYID, USUBJID, BASETYPE, PARAMCD),
+      order = exprs(ADT, VISITNUM, LBSEQ),
+      new_var = ABLFL,
+      mode = "last"
+    ),
+    filter = (!is.na(AVAL) & ADT <= TRTSDT & !is.na(BASETYPE))
+  )
+
+## Derive baseline information ----
+adlb <- adlb %>%
+  # Calculate BASE
+  derive_var_base(
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    source_var = AVAL,
+    new_var = BASE
+  ) %>%
+  # Calculate BASEC
+  derive_var_base(
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    source_var = AVALC,
+    new_var = BASEC
+  ) %>%
+  # Calculate BNRIND
+  derive_var_base(
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    source_var = ANRIND,
+    new_var = BNRIND
+  ) %>% # nolint start
+  # Calculate CHG for post-baseline records
+  # The decision on how to populate pre-baseline and baseline values of CHG is left to producer choice
+  # nolint end
+  restrict_derivation(
+    derivation = derive_var_chg,
+    filter = AVISITN > 0
+  ) %>% # nolint start
+  # Calculate PCHG for post-baseline records
+  # The decision on how to populate pre-baseline and baseline values of PCHG is left to producer choice
+  # nolint end
+  restrict_derivation(
+    derivation = derive_var_pchg,
+    filter = AVISITN > 0
+  )
+
+## Calculate lab grading ----
+
+# Assign ATOXDSCL and ATOXDSCH to hold lab grading terms
+# ATOXDSCL and ATOXDSCH hold terms defined by NCI-CTCAEv4.
+# See (https://pharmaverse.github.io/admiral/articles/lab_grading.html#implement_ctcv4)
+grade_lookup <- tibble::tribble(
+  ~PARAMCD, ~ATOXDSCL, ~ATOXDSCH,
+  "ALB", "Hypoalbuminemia", NA_character_,
+  "ALKPH", NA_character_, "Alkaline phosphatase increased",
+  "ALT", NA_character_, "Alanine aminotransferase increased",
+  "AST", NA_character_, "Aspartate aminotransferase increased",
+  "BILI", NA_character_, "Blood bilirubin increased",
+  "CA", "Hypocalcemia", "Hypercalcemia",
+  "CHOLES", NA_character_, "Cholesterol high",
+  "CK", NA_character_, "CPK increased",
+  "CREAT", NA_character_, "Creatinine increased",
+  "GGT", NA_character_, "GGT increased",
+  "GLUC", "Hypoglycemia", "Hyperglycemia",
+  "HGB", "Anemia", "Hemoglobin increased",
+  "POTAS", "Hypokalemia", "Hyperkalemia",
+  "LYMPH", "CD4 lymphocytes decreased", NA_character_,
+  "PHOS", "Hypophosphatemia", NA_character_,
+  "PLAT", "Platelet count decreased", NA_character_,
+  "SODIUM", "Hyponatremia", "Hypernatremia",
+  "WBC", "White blood cell decreased", "Leukocytosis",
+)
+
+# Assign grade criteria
+# metadata atoxgr_criteria_ctcv4 used to implement NCI-CTCAEv4
+# user could change to atoxgr_criteria_ctcv5 to implement NCI-CTCAEv5
+# Note: Hyperglycemia and Hypophosphatemia not defined in NCI-CTCAEv5 so
+# user would need to amend look-up table grade_lookup
+# See (https://pharmaverse.github.io/admiral/articles/lab_grading.html#implement_ctcv5)
+grade_crit <- atoxgr_criteria_ctcv4
+
+
+# Add ATOXDSCL and ATOXDSCH
+adlb <- adlb %>%
+  derive_vars_merged(
+    dataset_add = grade_lookup,
+    by_vars = exprs(PARAMCD)
+  ) %>%
+  # Derive toxicity grade for low values ATOXGRL
+
+  derive_var_atoxgr_dir(
+    meta_criteria = grade_crit,
+    new_var = ATOXGRL,
+    tox_description_var = ATOXDSCL,
+    criteria_direction = "L",
+    get_unit_expr = extract_unit(PARAM)
+  ) %>%
+  # Derive toxicity grade for low values ATOXGRH
+  # default metadata atoxgr_criteria_ctcv4 used
+  derive_var_atoxgr_dir(
+    meta_criteria = grade_crit,
+    new_var = ATOXGRH,
+    tox_description_var = ATOXDSCH,
+    criteria_direction = "H",
+    get_unit_expr = extract_unit(PARAM)
+  ) %>%
+  # (Optional) derive overall grade ATOXGR (combining ATOXGRL and ATOXGRH)
+  derive_var_atoxgr() %>%
+  # Derive baseline toxicity grade for low values BTOXGRL
+  derive_var_base(
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    source_var = ATOXGRL,
+    new_var = BTOXGRL
+  ) %>%
+  # Derive baseline toxicity grade for high values BTOXGRH
+  derive_var_base(
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    source_var = ATOXGRH,
+    new_var = BTOXGRH
+  ) %>%
+  # Derive baseline toxicity grade for for overall grade BTOXGR
+  derive_var_base(
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    source_var = ATOXGR,
+    new_var = BTOXGR
+  )
+
+
+## Calculate R2BASE, R2ANRLO and R2ANRHI ----
+adlb <- adlb %>%
+  derive_var_analysis_ratio(
+    numer_var = AVAL,
+    denom_var = BASE
+  ) %>%
+  derive_var_analysis_ratio(
+    numer_var = AVAL,
+    denom_var = ANRLO
+  ) %>%
+  derive_var_analysis_ratio(
+    numer_var = AVAL,
+    denom_var = ANRHI
+  )
+
+## SHIFT derivation ----
+adlb <- adlb %>%
+  # Derive shift from baseline for analysis indicator
+  derive_var_shift(
+    new_var = SHIFT1,
+    from_var = BNRIND,
+    to_var = ANRIND
+  ) %>%
+  # Derive shift from baseline for overall grade
+  restrict_derivation(
+    derivation = derive_var_shift,
+    args = params(
+      new_var = SHIFT2,
+      from_var = BTOXGR,
+      to_var = ATOXGR
+    ),
+    filter = !is.na(ATOXDSCL) | !is.na(ATOXDSCH)
+  )
+
+## Flag variables (ANL01FL, LVOTFL) ----
+# ANL01FL: Flag last result within an AVISIT for post-baseline records
+# LVOTFL: Flag last valid on-treatment record
+adlb <- adlb %>%
+  restrict_derivation(
+    derivation = derive_var_extreme_flag,
+    args = params(
+      by_vars = exprs(USUBJID, PARAMCD, AVISIT),
+      order = exprs(ADT, AVAL),
+      new_var = ANL01FL,
+      mode = "last"
+    ),
+    filter = !is.na(AVISITN) & ONTRTFL == "Y"
+  ) %>%
+  restrict_derivation(
+    derivation = derive_var_extreme_flag,
+    args = params(
+      by_vars = exprs(USUBJID, PARAMCD),
+      order = exprs(ADT, AVAL),
+      new_var = LVOTFL,
+      mode = "last"
+    ),
+    filter = ONTRTFL == "Y"
+  )
+
+## Get treatment information ----
+# See also the "Visit and Period Variables" vignette
+# (https://pharmaverse.github.io/admiral/articles/visits_periods.html#treatment_bds)
+adlb <- adlb %>%
+  # Assign TRTA, TRTP
+  mutate(
+    TRTP = TRT01P,
+    TRTA = TRT01A
+  )
+
+## Get extreme values ----
+adlb <- adlb %>%
+  # get MINIMUM value
+  derive_extreme_records(
+    dataset_add = adlb,
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    order = exprs(AVAL, ADT, AVISITN),
+    mode = "first",
+    filter_add = (!is.na(AVAL) & ONTRTFL == "Y"),
+    set_values_to = exprs(
+      AVISITN = 9997,
+      AVISIT = "POST-BASELINE MINIMUM",
+      DTYPE = "MINIMUM"
+    )
+  ) %>%
+  # get MAXIMUM value
+  derive_extreme_records(
+    dataset_add = adlb,
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    order = exprs(desc(AVAL), ADT, AVISITN),
+    mode = "first",
+    filter_add = (!is.na(AVAL) & ONTRTFL == "Y"),
+    set_values_to = exprs(
+      AVISITN = 9998,
+      AVISIT = "POST-BASELINE MAXIMUM",
+      DTYPE = "MAXIMUM"
+    )
+  ) %>%
+  # get LOV value
+  derive_extreme_records(
+    dataset_add = adlb,
+    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
+    order = exprs(ADT, AVISITN),
+    mode = "last",
+    filter_add = (ONTRTFL == "Y"),
+    set_values_to = exprs(
+      AVISITN = 9999,
+      AVISIT = "POST-BASELINE LAST",
+      DTYPE = "LOV"
+    )
+  )
+
+## Get ASEQ ----
+adlb <- adlb %>%
+  # Calculate ASEQ
+  derive_var_obs_number(
+    new_var = ASEQ,
+    by_vars = exprs(STUDYID, USUBJID),
+    order = exprs(PARAMCD, ADT, AVISITN, VISITNUM),
+    check_type = "error"
+  )
+
+# Add all ADSL variables
+adlb <- adlb %>%
+  derive_vars_merged(
+    dataset_add = select(adsl, !!!negate_vars(adsl_vars)),
+    by_vars = exprs(STUDYID, USUBJID)
+  )
+
+# Final Steps, Select final variables and Add labels
+# This process will be based on your metadata, no example given for this reason
+# ...
+
+# Save output ----
+
+# Change to whichever directory you want to save the dataset in
+dir <- tools::R_user_dir("admiral_templates_data", which = "cache")
+if (!file.exists(dir)) {
+  # Create the folder
+  dir.create(dir, recursive = TRUE, showWarnings = FALSE)
+}
+save(adlb, file = file.path(dir, "adlb.rda"), compress = "bzip2")
diff --git a/data-raw/create_admiral_adlb.R b/data-raw/create_admiral_adlb.R
new file mode 100644
index 0000000000..779d912e17
--- /dev/null
+++ b/data-raw/create_admiral_adlb.R
@@ -0,0 +1,111 @@
+#  Create dataset:   data/admiral_adlb.rda
+#  This script:  create_admiral_adlb.R creates dataset data/admiral_adlb.rda.
+#
+
+# Preliminary
+library(diffdf) # nolint
+
+# To clarify directories (can be removed)
+# nolint start: object_name_linter
+CACHE_DIR <- "~/.cache/R/admiral_templates_data/"
+DATA_DIR <- "data-dir"
+DATA_RAW <- "data-raw"
+TEMPLATE_DIR <- "inst/templates/"
+
+# clean CACHE_DIR
+THE_FILE <- paste0(CACHE_DIR, "/adlb.rda")
+THE_FILE <- paste0(CACHE_DIR, "/adsl.rda")
+if (file.exists(THE_FILE)) file.remove(THE_FILE)
+# nolint end
+
+#
+# STEPS
+#
+# First, use template to create the R script (in data-raw/admiral_adlb.R).
+# Next, source this script and create the data (~/.cache/R/admiral_template_data/admiral_adlb.rda)
+# Finally, shorten this data (now ~ 1.2 MB) by selecting only certain USUBJID
+
+# orignal method  - OMIT
+if (FALSE) {
+  # ### original mehtod (method 1)
+  # # First,  create the R script (from a template)
+  adam_name <- "adlb"
+  save_path <- paste0("./data-raw/admiral_", adam_name, ".R")
+  use_ad_template(
+    adam_name = adam_name,
+    save_path = save_path,
+    open = FALSE,
+    overwrite = TRUE
+  )
+  # Second, source the script and save data in .cache
+  source("data-raw/admiral_adlb.R") # nolint
+  load("~/.cache/R/admiral_templates_data/adlb.rda")
+}
+
+#
+# Instead, USE template, as recommened by Buzz
+#
+source(paste0(TEMPLATE_DIR, "/ad_adlb.R")) # nolint
+load(paste0(CACHE_DIR, "adlb.rda"))
+
+#
+# limit rows, by selecting only these USUBJID
+#
+#' 01-701-1015, 01-701-1023, 01-701-1028, 01-701-1033,
+#' 01-701-1034, 01-701-1047, 01-701-1097, 01-705-1186,
+#' 01-705-1292, 01-705-1310, 01-708-1286
+
+usubjid <-
+  c(
+    "01-701-1015",
+    "01-701-1023",
+    "01-701-1028",
+    "01-701-1033",
+    "01-701-1034",
+    "01-701-1047",
+    "01-701-1097",
+    "01-705-1186",
+    "01-705-1292",
+    "01-705-1310",
+    "01-708-1286"
+  )
+
+#  prepare for inner join
+user <- tibble(
+  USUBJID = usubjid
+)
+result <- inner_join(adlb, user)
+admiral_adlb <- result
+admiral_adlb
+
+#
+# Finally, save reduced ds
+#
+use_data(admiral_adlb, overwrite = TRUE)
+
+#
+#  TEST - is dataset identical to .... backup of unaltered dataset
+#
+e1 <- new.env()
+e2 <- new.env()
+load("data/admiral_adlb.rda", e1)
+
+# CHANGE to YOUR location of original dataset
+load("data-backup/admiral_adlb.rda", e2)
+
+# compare field names
+t <- tibble(e1 = names(e1$admiral_adlb), e2 = names(e2$admiral_adlb))
+t |> print(n = 111)
+
+identical(e1$admiral_adlb, e2$admiral_adlb)
+diffdf(e1$admiral_adlb, e2$admiral_adlb)
+
+## Capture diffdf to file
+
+capture.output(
+  diffdf(
+    compare = e1$admiral_adlb, base = e2$admiral_adlb,
+    keys = c("STUDYID", "DOMAIN", "USUBJID", "AVAL", "VISIT")
+  ),
+  file = "data-raw/diffdf_adlb_23SEPT"
+)
diff --git a/data-raw/create_admiral_adsl.R b/data-raw/create_admiral_adsl.R
new file mode 100644
index 0000000000..2649141e10
--- /dev/null
+++ b/data-raw/create_admiral_adsl.R
@@ -0,0 +1,78 @@
+#  Create dataset:   data/admiral_adsl.rda
+#  This script:  create_admiral_adsl.R creates dataset data/admiral_adsl.rda.
+#
+
+# Preliminary
+library(diffdf) # nolint
+
+
+# nolint start: object_name_linter.
+# To clarify directories (can be removed)
+CACHE_DIR <- "~/.cache/R/admiral_templates_data/"
+DATA_DIR <- "data-dir"
+DATA_RAW <- "data-raw"
+TEMPLATE_DIR <- "inst/templates/"
+
+# clean CACHE_DIR
+THE_FILE <- paste0(CACHE_DIR, "/adlb.rda")
+THE_FILE <- paste0(CACHE_DIR, "/adsl.rda")
+if (file.exists(THE_FILE)) file.remove(THE_FILE)
+# nolint end
+
+#
+# STEPS
+#
+# First, use template to create the R script (in data-raw/admiral_adlb.R).
+# Next, source this script and create the data (~/.cache/R/admiral_template_data/admiral_adlb.rda)
+# Finally, shorten this data (now ~ 1.2 MB) by selecting only certain USUBJID
+
+# OMIT -- orignal method  - OMIT
+if (FALSE) {
+  # ### original mehtod (method 1)
+  # # First,  create the R script (from a template)
+  adam_name <- "adlb"
+  save_path <- paste0("./data-raw/admiral_", adam_name, ".R")
+  use_ad_template(
+    adam_name = adam_name,
+    save_path = save_path,
+    open = FALSE,
+    overwrite = TRUE
+  )
+  # Second, source the script and save data in .cache
+  source("data-raw/admiral_adlb.R") # nolint
+  load("~/.cache/R/admiral_templates_data/adlb.rda")
+}
+
+#
+#
+# Instead, USE template, as recommened by Buzz
+#
+source(paste0(TEMPLATE_DIR, "/ad_adsl.R")) # nolint
+load(paste0(CACHE_DIR, "adsl.rda"))
+admiral_adsl <- adsl
+
+#
+# Finally, save reduced ds
+#
+use_data(admiral_adsl, overwrite = TRUE)
+
+#
+#  TEST - is dataset identical to .... backup of unaltered dataset
+#
+e1 <- new.env()
+e2 <- new.env()
+load("data/admiral_adsl.rda", e1)
+
+# CHANGE to YOUR location of original dataset
+load("data-backup/admiral_adsl.rda", e2)
+
+
+identical(e1$admiral_adsl, e2$admiral_adsl)
+diffdf(compare = e1$admiral_adsl, base = e2$admiral_adsl, keys = c("STUDYID", "USUBJID"))
+capture.output(
+  diffdf(
+    compare = e1$admiral_adsl, base = e2$admiral_adsl,
+    keys = c("STUDYID", "USUBJID")
+  ),
+  file = "data-raw/diffdf_23SEPT"
+)
diff --git a/inst/example_scripts/derive_single_dose.R b/data-raw/derive_single_dose.R
similarity index 93%
rename from inst/example_scripts/derive_single_dose.R
rename to data-raw/derive_single_dose.R
index d840653bdf..ff7cc9d29a 100644
--- a/inst/example_scripts/derive_single_dose.R
+++ b/data-raw/derive_single_dose.R
@@ -1,6 +1,9 @@
+# nolint start: undersiderable_function_linter
 library(pharmaversesdtm)
 library(admiral)
 library(dplyr)
+# nolint end
+
 ex <- pharmaversesdtm::ex
 
 # check that there is only one start/end date of exposure per subject and visit
@@ -52,4 +55,4 @@ attr(ex_single$EXSTDTC, "label") <- attr(ex$EXSTDTC, "label")
 attr(ex_single$EXENDTC, "label") <- attr(ex$EXENDTC, "label")
 attr(ex_single$EXDOSFRQ, "label") <- attr(ex$EXDOSFRQ, "label")
 
-save(ex_single, file = file.path("data", "ex_single.rda"), compress = "bzip2")
+usethis::use_data(ex_single, overwrite = TRUE)
diff --git a/inst/example_scripts/example_qs.R b/data-raw/example_qs.R
similarity index 98%
rename from inst/example_scripts/example_qs.R
rename to data-raw/example_qs.R
index f6c6e7ab3a..1286e93352 100644
--- a/inst/example_scripts/example_qs.R
+++ b/data-raw/example_qs.R
@@ -1,4 +1,8 @@
-library(dplyr)
+## Code to create `example_qs.rda` dataset and save it in data/
+## This replaces inst/example_scripts/example_qs.R
+## Follows the same standard as pharmaversesdtm
+
+
 # nolint start
 suppress_warning(
   qs_gad7 <- tibble::tribble(
@@ -202,5 +206,5 @@ example_qs <- bind_rows(qs_gad7, qs_gdssf, qs_sp) %>%
     STUDYID = "STUDYX",
     .before = everything()
   )
-
-save(example_qs, file = file.path("data", "example_qs.rda"), compress = "bzip2")
+#  create example_qs.rda in data/
+usethis::use_data(example_qs, overwrite = TRUE)
diff --git a/inst/example_scripts/example_query_source.R b/data-raw/example_query_source.R
similarity index 100%
rename from inst/example_scripts/example_query_source.R
rename to data-raw/example_query_source.R
diff --git a/data/admiral_adlb.rda b/data/admiral_adlb.rda
index 9bf8663e65..485940b76b 100644
Binary files a/data/admiral_adlb.rda and b/data/admiral_adlb.rda differ
diff --git a/data/admiral_adsl.rda b/data/admiral_adsl.rda
index 79f5921fdb..061a959380 100644
Binary files a/data/admiral_adsl.rda and b/data/admiral_adsl.rda differ
diff --git a/data/atoxgr_criteria_ctcv4.rda b/data/atoxgr_criteria_ctcv4.rda
index eee2737efb..35c00d7a94 100644
Binary files a/data/atoxgr_criteria_ctcv4.rda and b/data/atoxgr_criteria_ctcv4.rda differ
diff --git a/data/atoxgr_criteria_ctcv5.rda b/data/atoxgr_criteria_ctcv5.rda
index 1671095608..5d4df887e2 100644
Binary files a/data/atoxgr_criteria_ctcv5.rda and b/data/atoxgr_criteria_ctcv5.rda differ
diff --git a/data/atoxgr_criteria_daids.rda b/data/atoxgr_criteria_daids.rda
index 17aee71787..31934ec248 100644
Binary files a/data/atoxgr_criteria_daids.rda and b/data/atoxgr_criteria_daids.rda differ
diff --git a/data/ex_single.rda b/data/ex_single.rda
index ae359ca0db..c0db6a6d81 100644
Binary files a/data/ex_single.rda and b/data/ex_single.rda differ
diff --git a/data/example_qs.rda b/data/example_qs.rda
index df81153271..7274ba7665 100644
Binary files a/data/example_qs.rda and b/data/example_qs.rda differ
diff --git a/inst/WORDLIST b/inst/WORDLIST
index 23746554ac..e3a009b79f 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -189,6 +189,7 @@ Pharmaverse
 Phosphatase
 Pooja
 Pre
+Premarketing
 QD
 QID
 README
diff --git a/man/admiral_adsl.Rd b/man/admiral_adsl.Rd
index dabde0e714..dc73f839aa 100644
--- a/man/admiral_adsl.Rd
+++ b/man/admiral_adsl.Rd
@@ -5,7 +5,7 @@
 \alias{admiral_adsl}
 \title{Subject Level Analysis Dataset}
 \format{
-An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 306 rows and 50 columns.
+An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 306 rows and 54 columns.
 }
 \source{
 Derived from the \code{dm} and \code{ds} datasets using \code{{admiral}} (\url{https://github.com/pharmaverse/admiral/blob/main/inst/templates/ad_adsl.R})
diff --git a/vignettes/hys_law.Rmd b/vignettes/hys_law.Rmd
index 2f6bdea729..ad67a0a475 100644
--- a/vignettes/hys_law.Rmd
+++ b/vignettes/hys_law.Rmd
@@ -13,12 +13,15 @@ knitr::opts_chunk$set(
   comment = "#>"
 )
 
+library(admiral)
 library(admiraldev)
 ```
 
 # Introduction
 
-During the drug development process, clinical trials are often required to assess for the potential that the experimental drug can cause severe liver injury, known as a drug induced liver injury [(DILI)](https://www.fda.gov/media/116737/download). There are multiple criteria that need to be evaluated to determine and classify a DILI "Event". Hy's Law, a common rule of thumb for a DILI Event , is usually comprised of three parts:
+During the drug development process, clinical trials are often required to assess for the potential that the experimental drug can cause severe liver injury, known as a drug induced liver injury (DILI)  [Drug-Induced Liver Injury:
+Premarketing Clinical
+Evaluation](https://www.fda.gov/media/116737/download). There are multiple criteria that need to be evaluated to determine and classify a DILI "Event". Hy's Law, a common rule of thumb for a DILI Event , is usually comprised of three parts:
 
 - Elevated alanine aminotransferase (ALT) or aspartate aminotransferase (AST) by 3-times or greater of the upper limit of normal.
 - Elevated serum total bilirubin (BILI) by 2-times or greater within a window of time, ~14 days after the elevated ALT/AST event.